一类异采样率双环SISO网络控制系统的建模及稳定性研究

本文研究了一类具有异采样率双环的单输入单输出网络控制系统的建模和稳定性问题。传统的单环控制无法更好的满足对控制系统的高要求,而双闭环的控制方式又是生产控制中普遍存在的。该类网络控制系统是一个双回路闭环系统,所考虑的时延大于外环采样周期的固定时延,推导出了该类网络控制系统的多时滞离散时间数学模型,并利用李雅普诺夫定理和自由权矩阵法,分析了系统的渐近稳定性,给出了系统稳定的条件。最后,通过仿真证明了结果的有效性。     

网络控制系统中网络时延与建模分析

网络技术的广泛应用,对控制理论的研究提出了挑战,同时也带来了崭新的研究机遇和发展空间.本文从网络控制系统的特点和要求出发,对网络时延及其对网络控制系统的影响进行了阐述,并与建模分析相结合,利用连续和离散系统理论建立了几种较为常用的网络控制系统数学模型.在建模过程中考虑了控制器的动态特性、不同的网络时延和不同的节点工作方式,为网络控制系统的分析、仿真和控制器的设计奠定了一定的理论基础.     

基于马尔可夫模型的NCS可靠性分析

基于传统可靠性理论的研究,提出了一种Markov模型的网络控制系统可靠性评估方法及其建模过程.该方法通过详细分析工业网络控制系统的特殊性,构建网络控制系统的可靠性状态图,以推导系统的查普曼-科尔莫戈罗夫(Chapman-Kolmoqorov)方程,得到工业网络控制系统的可靠度模型,为网络控制系统进一步应用于国民经济众多领域奠定基础.     

网络控制系统的鲁棒H∞保成本状态反馈控制

针对有不确定网络诱导时延的网络控制系统,本文研究了鲁棒H∞保成本状态反馈控制律的设计问题。首先通过数学推导将网络诱导时延的不确定性转化为参数的不确定性,然后基于李雅普诺夫稳定性定理,以线性矩阵不等式(LMI)的形式推导出使闭环系统无扰动时鲁棒渐近稳定并具有一定性能的状态反馈控制律的形式,进而在系统有扰动时设计了γ次优鲁棒H∞状态反馈控制律。     

输出反馈的网络控制系统建模方法比较

针对时延、丢包及被控对象仅输出可测量的一类网络控制系统,设计了适合网络环境的状态观测器,并利用状态观测器对时延和丢包进行补偿。然后分别介绍了两种不同的建模方法:离散时间建模方法和离散与连续相结合的建模方法。并对两种方法进行了比较。     

短时延网络控制系统的研究现状

近年来,网络控制系统得到越来越多的关注,其主要挑战之一在于控制环中的网络时延对其影响,文章论述了短时延的网络控制系统现有的一些研究方法随机控制方法、时延补偿的方法、预测控制方法;并指出这种问题其他可能的一些研究方法.     

基于预测控制的网络时延补偿策略研究

针对网络控制系统(NCS)中的时延问题,在分析网络时延特性的基础上,本文提出对系统采用预测控制策略进行时延补偿.为克服网络控制系统中时钟不易精确同步的问题,该策略用易于测昔的网络往返时延代替不易单独测量的前向时延和后向时延,不但采用MATLAB/TrueTime仿真工具箱对实际系统进行了仿真研究,还使用网络实验控制平台对实际的电机控制系统进行了实验研究.仿真和实验结果表明,该策略可以对网络时延进行精确补偿,保证网络控制系统具有良好性能.     

一类网络控制系统的稳定性分析

在基于多包传输的网络控制系统中,传感器采用时间驱动,控制器和执行器采用事件驱动.假定传输时延可以忽略,则整个网络控制系统可以描述为一个具有N个事件的异步动态系统.该文针对受控对象状态均可测,控制律采用输出反馈的情况,利用双线性矩阵不等式方法,讨论了网络控制系统指数稳定的问题,并给出了稳定性的充分条件,最后通过仿真实验加以验证.     

分布式无线网络下的多移动机器人控制系统

根据移动机器人的控制要求设计实现一个基于分布式无线网络条件下的多移动机器人控制系统.采用多节点连接方式的网络拓扑结构将多个机器人或其它设备连接组成机器人控制网络.机器人控制采用分层递阶的结构,并根据网络控制系统的特点和要求特别是在时延的特点上进行优化.控制系统实现了一定的自主决策并能体现出一定的智能性.通过对不同网络条件下机器人控制过程的时延进行了测试,根据实际实验数据分析评价了分布式无线网络控制系统的可行性与实际控制效果.     

基于逆系统方法的起重机网络远程控制策略

以起重机为网络远程控制对象,基于逆系统方法设计了起重机速度和磁通的解耦伪线性系统;并对此伪线性系统引入了线性反馈.针对网络控制系统中存在的网络诱导时延问题,建立了基于网络的起重机闭环系统模型,并以此为基础设计了速度和磁通的滑模控制器.利用Lyapunov定理证明,设计的控制器能够使系统状态收敛于滑模面,并能够保证闭环网络控制?破 系统全局稳定,仿真结果验证了该控制策略的有效性.     

Extended dissipative state estimation for uncertain discrete-time Markov jump neural networks with mixed time delays

This paper is concerned with the problem of extended dissipativity-based state estimation for uncertain discrete-time Markov jump neural networks with finite piecewise homogeneous Markov chain and mixed time delays. The aim of this paper is to present a Markov switching estimator design method, which ensures that the resulting error system is extended stochastically dissipative. A triple-summable term is introduced in the constructed Lyapunov function and the reciprocally convex approach is utilized to bound the forward difference of the triple-summable term. The extended dissipativity criterion is derived in form of linear matrix inequalities. Numerical simulations are conducted to demonstrate the effectiveness of the proposed method.     

Global exponential stability of neutral high-order stochastic Hopfield neural networks with Markovian jump parameters and mixed time delays

In this paper, a class of neutral high-order stochastic Hopfield neural networks with Markovian jump parameters and mixed time delays is investigated. The jumping parameters are modeled as a continuous-time finite-state Markov chain. At first, the existence of equilibrium point for the addressed neural networks is studied. By utilizing the Lyapunov stability theory, stochastic analysis theory and linear matrix inequality (LMI) technique, new delay-dependent stability criteria are presented in terms of linear matrix inequalities to guarantee the neural networks to be globally exponentially stable in the mean square. Numerical simulations are carried out to illustrate the main results.     

基于执行器部分失效的网络化控制系统完整性研究

针对一类具有马尔可夫特性时延的网络化控制系统,考虑系统参数不确定性的影响,基于时延T-S模糊模型建立数学模型,通过构造离散Lyapunov函数,推证出了确保网络化控制系统在执行器部分失效时具有鲁棒完整性的充分条件,并以求解LMIs给出容错控制器的设计方法.最后通过仿真验证了文中所述方法的可行性和有效性.     

Networked control of industrial automation systems—a new predictive method

A new method for real-time prediction of uncertain network transmission time delays and a method for closed-loop control of manufacturing and industrial plants through networks are introduced. The proposed delay prediction method is based on the multilayer perceptron neural model. In order to minimize the number of neurons in the first layer of the network and hence reducing the computational burden in a real-time implementation, a method for determination of the Markov order of the time delay sequence is presented. Using the predicted delay, and a zero-order hold equivalent discrete-time model of the plant, a time varying state feedback control algorithm with a real-time gain updating strategy is proposed. A sufficient condition for closed-loop stability is also derived using the switching theorem for linear systems. The proposed method is shown, through two industrial networked case studies, namely, a DC motor driving a transportation roller for paper sheets and a milling machine. Simulation studies depict the efficacy of the proposed method in controlling such challenging problems.     

Gain-scheduling multivariable LPV control of an irrigation canal system

The purpose of this paper is to present a multivariable linear parameter varying (LPV) controller with a gain scheduling Smith Predictor (SP) scheme applicable to open-flow canal systems. This LPV controller based on SP is designed taking into account the uncertainty in the estimation of delay and the variation of plant parameters according to the operating point. This new methodology can be applied to a class of delay systems that can be represented by a set of models that can be factorized into a rational multivariable model in series with left/right diagonal (multiple) delays, such as, the case of irrigation canals. A multiple pool canal system is used to test and validate the proposed control approach.     

Robust absolute stability criteria for uncertain Lurie interval time-varying delay systems of neutral type

This study investigates the delay-dependent robust absolute stability analysis for uncertain Lurie systems with interval time-varying delays of neutral type. First, we divide the whole delay interval into two segmentations with an unequal width and checking the variation of the Lyapunov–Krasovskii functional (LKF) for each subinterval of delay, much less conservative delay-dependent absolute and robust stability criteria are derived. Second, a new delay-dependent robust stability condition for uncertain Lurie neutral systems with interval time-varying delays, which expressed in terms of quadratic forms of linear matrix inequalities (LMIs), and has been derived by constructing the LKF from the delayed decomposition approach (DDA) and integral inequality approach (IIA). Finally, three numerical examples are given to show the effectiveness of the proposed stability criteria.     

A delay decomposition approach to robust stability analysis of uncertain systems with time-varying delay

This paper is concerned with delay-dependent robust stability for uncertain systems with time-varying delays. The proposed method employs a suitable Lyapunov-Krasovskii's functional for new augmented system. Then, based on the Lyapunov method, a delay-dependent robust criterion is devised by taking the relationship between the terms in the Leibniz-Newton formula into account. By developing a delay decomposition approach, the information of the delayed plant states can be taken into full consideration, and new delay-dependent sufficient stability criteria are obtained in terms of linear matrix inequalities (LMIs) which can be easily solved by various optimization algorithms. Numerical examples are included to show that the proposed method is effective and can provide less conservative results.     

Admissibility analysis for linear singular systems with time-varying delays via neutral system approach

This paper studies the admissibility problem for a class of linear singular systems with time-varying delays. In order to highlight the relations between the delay and the state, the singular system is transformed into a neutral form. Then, an appropriate type of Lyapunov–Krasovskii functionals is proposed to develop a delay-derivative-dependent admissibility condition in terms of linear matrix inequalities. The derivation combines the Wirtinger-based inequality and reciprocally convex combination method. The present criterion is also for the stability test of retarded and neutral systems with time-varying delays. Some examples are provided to illustrate the effectiveness and the benefits of the proposed method.     

Robust stability of some oscillatory systems including time-varying delay with applications in congestion control

This paper focuses on the stability of some second-order linear systems with multiple constant and time-varying delays, under the assumption that the corresponding system without delays is an oscillator. Sufficient conditions for delay-dependent stability will be derived using the integral quadratic constraint approach combined with the generalized eigenvalue distribution of some appropriate finite-dimensional matrix pencils. As applications, we shall discuss some fluid approximation models used in congestion control of high-speed networks, under the natural assumptions that the control-time intervals are constant, but the round-trip times are time-varying.     

Stochastic stability and stabilization of Markov jump linear systems with instantly time-varying transition rates: A unified framework

This paper investigates the stochastic stability and stabilization problems of non-homogeneous Markov jump linear systems (NHMJLSs) characterized by instantly unconditionally time-varying transition rates (TRs). The novelty of the study lies in proposing a systematic method for achieving finite dimensional conditions with an acceptable degree of conservativeness for the stability and the stabilization problems of the system. In this framework, by first processing the time-varying TRs, a finite number of uncertain but time-constant TR matrices are obtained. Then, a high-level switching signal is constructed for the system, which models the contribution of each possible time-constant TR matrix. Based on the results, the NHMJLS is reformed into an uncertain switching structure referred to as the associated switched Markov jump linear system (AS-MJLS). Finally, by taking advantage of the new representation, sufficient conditions are obtained to ensure the stability and stabilizability of the system, also the controller gains are designed. The proposed framework provides a realistic representation as well as practically solvable analysis and synthesis conditions for the NHMJLS. It also leads to less conservative results compared with the existing well-known techniques. Comparative simulation studies for a single-machine infinite-bus (SMIB) power system subject to stochastically varying load demonstrate the efficiency and superiority of the method.